Literature DB >> 18281152

Biological treatment of highly contaminated acid mine drainage in batch reactors: Long-term treatment and reactive mixture characterization.

Carmen M Neculita1, Gérald J Zagury.   

Abstract

Passive bioreactors involving sulphate-reducing bacteria (SRB) are a practical alternative technology to treat acid mine drainage (AMD). Careful selection of the organic carbon source is important to ensure performance and long-term efficiency of the treatment. However, a rigorous and methodical characterization to predict the biodegradability of organic substrates by SRB still needs to be investigated. In the present study, four natural organic materials were thoroughly characterized to assess their ability to serve as substrates and to find a parameter that links organic carbon sources with their biodegradability. Three reactive mixtures were then comparatively evaluated for their performance to treat a highly contaminated AMD in long-term (152 days) batch experiments. All three mixtures were successful for sulphate reduction and metal (Fe, Ni, Cd, Zn, and Mn) removal (91.8-99.8%). Higher efficiencies were observed in the reactors with 30% (w/w) cellulosic wastes (maple wood chips and sawdust) which decreased sulphate concentrations from 5500 mg/L to <1mg/L, than in reactors with 2-3% cellulosic wastes, where final sulphate concentrations were in the range 2000-2750 mg/L. Organic material characterization indicated that higher C/N ratios, chemical oxygen demand (COD)/SO(4)(2-) ratios and dissolved organic carbon (DOC)/SO(4)(2-) ratios were associated with better sulphate-reducing conditions and metal removal. This work suggests that C/N and DOC/SO(4)(2-) ratios considered together are key parameters to assess the biodegradability of natural organic wastes under sulphate-reducing conditions.

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Year:  2008        PMID: 18281152     DOI: 10.1016/j.jhazmat.2008.01.002

Source DB:  PubMed          Journal:  J Hazard Mater        ISSN: 0304-3894            Impact factor:   10.588


  7 in total

1.  Comparison of the efficiency of chitinous and ligneous substrates in metal and sulfate removal from mining-influenced water.

Authors:  Patricio X Pinto; Souhail R Al-Abed; John McKernan
Journal:  J Environ Manage       Date:  2018-09-07       Impact factor: 6.789

2.  Nickel, manganese and copper removal by a mixed consortium of sulfate reducing bacteria at a high COD/sulfate ratio.

Authors:  L P Barbosa; P F Costa; S M Bertolino; J C C Silva; R Guerra-Sá; V A Leão; M C Teixeira
Journal:  World J Microbiol Biotechnol       Date:  2014-04-08       Impact factor: 3.312

3.  Performance and bacterial communities of successive alkalinity-producing systems (SAPSs) in passive treatment processes treating mine drainages differing in acidity and metal levels.

Authors:  Sokhee Philemon Jung; Youngwook Cheong; Giljae Yim; Sangwoo Ji; Hojeong Kang
Journal:  Environ Sci Pollut Res Int       Date:  2013-11-27       Impact factor: 4.223

4.  Assessment of sulfide production risk in soil during the infiltration of domestic wastewater treated by a sulfur-utilizing denitrification process.

Authors:  L Ghorbel; L Coudert; Y Gilbert; G Mercier; J F Blais
Journal:  Environ Sci Pollut Res Int       Date:  2016-06-24       Impact factor: 4.223

5.  The microbial community of a passive biochemical reactor treating arsenic, zinc, and sulfate-rich seepage.

Authors:  Susan Anne Baldwin; Maryam Khoshnoodi; Maryam Rezadehbashi; Marcus Taupp; Steven Hallam; Al Mattes; Hamed Sanei
Journal:  Front Bioeng Biotechnol       Date:  2015-03-06

6.  Competitive Growth of Sulfate-Reducing Bacteria with Bioleaching Acidophiles for Bioremediation of Heap Bioleaching Residue.

Authors:  Aung Kyaw Phyo; Yan Jia; Qiaoyi Tan; Heyun Sun; Yunfeng Liu; Bingxu Dong; Renman Ruan
Journal:  Int J Environ Res Public Health       Date:  2020-04-15       Impact factor: 3.390

7.  Preparation of biologically activated lignite immobilized SRB particles and their AMD treatment characteristics.

Authors:  Junzhen Di; Yangyang Jiang; Mingjia Wang; Yanrong Dong
Journal:  Sci Rep       Date:  2022-03-10       Impact factor: 4.379

  7 in total

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